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Configures an Agno AI agent with all its dependencies — model, tools, knowledge base, memory, and storage.

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Config

FieldTypeRequiredDefaultDescription
namestringNoResource nameDisplay name for the agent
descriptionstringNo—Agent description
rolestringNo—Agent role description
modelDependencyYes—Reference to agno/models/anthropic or agno/models/openai
instructionslist[string]No—System instructions for the agent
promptDependencyNo—Reference to agno/prompt for reusable instructions
toolslist[Dependency]No[]References to agno/tools/mcp or agno/tools/websearch
knowledgeDependencyNo—Reference to agno/knowledge
dbDependencyNo—Reference to agno/db/postgres for session storage
memoryDependencyNo—Reference to agno/memory/manager
markdownbooleanNofalseFormat responses as Markdown
add_datetime_to_contextbooleanNofalseInclude current datetime in context
read_chat_historybooleanNoAutoRead chat history from DB (auto-enabled when db is set)
add_history_to_contextbooleanNoAutoAdd history to context (auto-enabled when db is set)
num_history_runsintegerNo—Number of previous runs to include in history
enable_agentic_memorybooleanNofalseEnable agentic memory capabilities
update_memory_on_runbooleanNofalseUpdate memory after each run
add_memories_to_contextbooleanNo—Add stored memories to context
enable_session_summariesbooleanNofalseEnable session summary generation

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Outputs

FieldTypeDescription
specobjectSerialized agent specification for runtime reconstruction
pip_dependencieslist[string]Python packages required by agent tools and knowledge

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Dependencies

Depends on:
  • agno/models/anthropic or agno/models/openai (required) — the LLM powering the agent
  • agno/tools/mcp or agno/tools/websearch (optional) — tool integrations
  • agno/knowledge (optional) — semantic search knowledge base
  • agno/memory/manager (optional) — persistent memory
  • agno/db/postgres (optional) — session and chat history storage
  • agno/prompt (optional) — reusable prompt template
Depended on by:
  • agno/team — as a team member
  • agno/runner — for deployment to Kubernetes

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Example

provider: agno
resource: agent
name: my-assistant
config:
  description: "A helpful AI assistant"
  model:
    provider: agno
    resource: models/anthropic
    name: claude
  instructions:
    - "You are a helpful assistant."
    - "Always respond concisely."
  tools:
    - provider: agno
      resource: tools/websearch
      name: search
  markdown: true

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Notes

  • The agent resource is stateless — it produces a serializable spec used by agno/runner for deployment.
  • When db is set, read_chat_history and add_history_to_context are automatically enabled unless explicitly overridden.
  • Updating a dependency (e.g., changing the model) triggers the agent to rebuild automatically.